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How can we make international comparisons of infant mortality in high income countries based on aggregate data more relevant to policy?

Overview of attention for article published in BMC Pregnancy and Childbirth, December 2017
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Title
How can we make international comparisons of infant mortality in high income countries based on aggregate data more relevant to policy?
Published in
BMC Pregnancy and Childbirth, December 2017
DOI 10.1186/s12884-017-1622-z
Pubmed ID
Authors

Ania Zylbersztejn, Ruth Gilbert, Anders Hjern, Pia Hardelid

Abstract

Infant mortality rates are commonly used to compare the health of populations. Observed differences are often attributed to variation in child health care quality. However, any differences are at least partly explained by variation in the prevalence of risk factors at birth, such as low birth weight. This distinction is important for designing interventions to reduce infant mortality. We suggest a simple method for decomposing inter-country differences in crude infant mortality rates into two metrics representing risk factors operating before and after birth. We used data from 7 European countries participating in the EURO-PERISTAT project in 2010. We calculated crude and birth weight-standardised stillbirth and infant mortality rates using Norway as the standard population. We decomposed between-country differences in crude stillbirth and infant mortality rates into the within-country difference in crude and birth weight-standardised stillbirth and infant mortality rates (metric 1), reflecting prenatal risk factors, and the between-country difference in birth weight-standardised stillbirth and infant mortality rates (metric 2), reflecting risk factors operating after birth. We also calculated birth weight-specific mortality. Using our metrics, we showed that for England, Wales and Scotland risk factors before and after birth contributed equally to the differences in crude stillbirth and infant mortality rates relative to Norway. In Austria, Czech Republic and Switzerland the differences were driven primarily by metric 1, reflecting high rate of low birth weight. The highest values of metric 2 observed in Poland partially reflected high rates of congenital anomalies. Our suggested metrics can be used to guide policy decisions on preventing infant deaths through reducing risk factors at birth or improving the care of babies after birth. Aggregate data tabulated by birth weight/gestational age should be routinely collected and published in high-income countries where birth weight is reported on birth certificates.

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X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 42 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 42 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 24%
Researcher 5 12%
Student > Master 4 10%
Student > Bachelor 3 7%
Student > Postgraduate 2 5%
Other 1 2%
Unknown 17 40%
Readers by discipline Count As %
Medicine and Dentistry 11 26%
Social Sciences 6 14%
Nursing and Health Professions 3 7%
Psychology 2 5%
Mathematics 1 2%
Other 1 2%
Unknown 18 43%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 11 January 2018.
All research outputs
#14,961,684
of 23,012,811 outputs
Outputs from BMC Pregnancy and Childbirth
#2,882
of 4,238 outputs
Outputs of similar age
#254,138
of 440,404 outputs
Outputs of similar age from BMC Pregnancy and Childbirth
#90
of 109 outputs
Altmetric has tracked 23,012,811 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,238 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.8. This one is in the 28th percentile – i.e., 28% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 440,404 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 39th percentile – i.e., 39% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 109 others from the same source and published within six weeks on either side of this one. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.